Psychometric assessment and application of the Chinese version of the Compliance with Annual Diabetic Eye Exams Survey in people with diabetic retinopathy.

X Zhu, Y Xu,X Xu, J Zhu,X He,L Lu,H Zou

DIABETIC MEDICINE(2020)

引用 5|浏览7
暂无评分
摘要
Aim To translate the Compliance with Annual Diabetic Eye Exams Survey (CADEES) into Chinese, allowing assessment of its reliability and validity, and to identify variables that predict attendance at annual eye examinations. Methods People with vision-threatening diabetic retinopathy were recruited from the Shanghai Diabetic Eye Study. The study involved three phases: (1) translation and cross-cultural adaptation, (2) a pilot study (n = 496) to evaluate the psychometric properties of the Chinese-CADEES, and (3) a primary cross-sectional survey (n = 3818) to assess self-reported attendance at annual eye examinations. Factors related to non-attendance were identified using univariate analysis, and then a multiple logistic regression model. Finally, a component model and individual item models were built to predict attendance. Results The Chinese-CADEES had satisfactory reliability and validity. The issue of low attendance at annual eye examinations was serious. In addition to 13 health belief items, living in semi-urban suburban areas, shorter duration of diabetes, poor glucose control, lower education level, better presenting visual acuity and milder diabetic retinopathy diagnosis were significantly related to non-attendance. The multivariate predictive model was able to predict, with 64.7% accuracy, whether or not participants were going to attend annual eye examinations and explained 11.3% of the variance in attendance. Conclusions The Chinese-CADEES showed good reliability and validity for predicting attendance at annual eye examinations in people with diabetic retinopathy. Clinicians and researchers can improve attendance by addressing modifiable characteristics and increasing education on diabetic retinopathy and the importance of eye health in people with diabetes.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要